Data and agile – Key concepts behind the buzzwords all executives should know
Hepburn and Tracy. Gin and tonic. Yin and yang. Some pairs are just meant to be, especially when their combination is greater than the sum of their parts. Today, we should be adding “data” and “agile” to this list of inseparable pairs. While these buzzwords are each familiar in their own right, today it’s their combination that offers senior executives a powerful new process, and a fighting chance at not only surviving but even prospering in the new digital economy.
Collecting, visualizing and analyzing data has been a recent mainstay of the modern enterprise, generating critical insights enterprises need to improve performance and identify opportunities. Agile methods began in the automotive world, were adapted to accelerate software development, and now they’re being applied with increasing success throughout businesses and nonprofits alike.
Putting the two together – creating an agile environment for analyzing and acting on data-driven insights – is now leading to value creation and process improvements at a much quicker pace. This is replacing the outdated methods of basing priorities on intuition (instead of data) and then using a slower “waterfall” approach of designing, building and testing new product features and capabilities. What’s more, data insights can be supercharged when accompanied by the agile development processes.
Top executives who take action in combining data-driven decision-making and agile development methods in their organizations stand to benefit greatly from this powerful pairing.
Here are some of the core concepts involved in marrying data with agile methods:
Customer value creation
Outside-in Product Development. At dPrism, we advise clients to talk with current and potential customers to understand the types of data that will create value in their business (either by providing the data directly to customers or using it internally to benefit them). Then we tease out the variations, and understand how the organization will best gather, visualize and analyze their data – do they need a dashboard, a data feed, an application programming interface (API)?
Design thinking. Once data insights have been gathered, it’s time to design new products or capabilities. The best way to discover how to create sustainable and differentiating value in the marketplace is through an iterative design process that bridges imagination and implementation. Through rapid prototypes, organizations can address complex challenges, create value and grow.
Value Validation. Getting continuous feedback from customers and prospects is essential. Many teams, once underway, make the mistake of thinking they “know” what the customer wants and skip the research. Respect your team’s instincts, but don’t skip gathering the data that is required for a meaningful validation.
Establish your data capability
Create a capability vision. The design-thinking and validation stages above will help you determine who your customers are and what they need. Now: What core capabilities will you bring to market? And what data sources are needed to deliver them, both to your customers and to your team? Most likely you’ll quickly realize what you need will be three times bigger and more complicated than you imagined.
Choose the best platform(s). Capabilities include data storage, joining, analysis and visualization. Good solutions at various price points are available from the big vendors like Amazon (Amazon Athena & other solutions), Microsoft (Business Intelligence), IBM (Analytics) and Oracle (Analytics Cloud). And there are specialty providers like Tableau, Looker, Microstrategy, SAS, Rstudio and many others. A good place to read about these tools is G2Crowd.
Start small. Experiment, learn and improve. Some of the tools mentioned above lend themselves to experimenting and growing more than others. Get your known data sources into the platform, and serendipitously add adjacent or other connectable data. You’ll be surprised by what you can discover.
Experiment, iterate and productize
Experiment. The digital economy is a frontier. You will not know everything you will need to know. Understand there is no such thing as a “final design.” Instead, work toward a more general vision and learn from the experimentation. Test these experimentations with customers and prospects. Think in terms of regular delivery of incremental value (a key agile concept) rather than a finite finish line.
Iterate. Establish a strict iteration schedule and size the work to fit within the iteration. We’ve helped our clients learn to work in two-, three- and four-week iterations (or “sprints,” in agile lingo), and develop velocity (another agile concept) by making each iteration more efficient.
Productize. Once the iterations of experimentation get to a product that creates value for your customers, develop a go-to-market plan, establish the in-market product and operations, and consider beta pre-releases to test the reliability of the product. Seek constant constructive feedback from customers. And be transparent about planned improvements – it builds trust.
The worlds of data analytics and agile delivery are fast-moving – new technologies are released and improved daily. But today we know that “data” and “agile” can be synchronized to your organization’s advantage. So jump in. The biggest mistake a company can make is to hang onto the classic waterfall way of thinking, while taking years to get new products to market.
Any organization – including yours – can begin a meaningful shift into the new world of data-driven design, rapid iteration and continuous value delivery, and begin to see results, within three to six months. At the current pace of change, those who don’t start their journey today risk seeing their window of opportunity close much faster than they might think.